outbrain-inc/outrank
A Python library for efficient feature ranking and selection on sparse data sets.
This tool helps data scientists and machine learning engineers identify the most important features in large, complex datasets used for recommender systems. It takes in raw, sparse, and noisy categorical data and outputs a ranked list of features, highlighting those that are most relevant and helping to detect data quality issues. The goal is to build more compact and better-performing recommendation models faster.
Use this if you are building recommender systems and struggle to identify meaningful signals in large, sparse, and noisy datasets with many categorical features.
Not ideal if your data is not sparse or categorical, or if you are not working on recommender systems or AutoML-based model search.
Stars
23
Forks
7
Language
Python
License
BSD-3-Clause
Category
Last pushed
Mar 03, 2026
Commits (30d)
0
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